Collecting posture information to evaluate therapy

ABSTRACT

A medical device delivers a therapy to a patient. Posture events are identified, e.g., a posture of the patient is periodically determined and/or posture transitions by the patient are identified, and each determined posture event is associated with a current therapy parameter set. A value of at least one posture metric is determined for each of a plurality of therapy parameter sets based on the posture events associated with that therapy parameter set. A list of the therapy parameter sets is presented to a user, such as a clinician, for evaluation of the relative efficacy of the therapy parameter sets. The list may be ordered according to the one or more posture metric values to aid in evaluation of the therapy parameter sets. Where values are determined for a plurality of posture metrics, the list may be ordered according to the one of the posture metrics selected by the user.

This application is a divisional of U.S. application Ser. No.12/856,255, filed Aug. 13, 2010, which is a continuation of U.S.application Ser. No. 11/691,391, filed Mar. 26, 2007, now U.S. Pat. No.7,792,583, which is a continuation-in-part of U.S. application Ser. No.11/081,872, filed Mar. 16, 2005, now U.S. Pat. No. 7,447,545, which wasa continuation-in-part of U.S. application Ser. No. 10/826,926, filedApr. 15, 2004, now U.S. Pat. No. 7,330,760, which claimed the benefit ofU.S. provisional application No. 60/553,784, filed Mar. 16, 2004. U.S.application Ser. No. 11/691,391 also claimed the benefit of U.S.Provisional Application No. 60/785,820, filed Mar. 24, 2006. The entirecontent of each of these applications is incorporated herein byreference.

TECHNICAL FIELD

The invention relates to medical devices and, more particularly, tomedical devices that deliver therapy.

BACKGROUND

In some cases, an ailment may affect a patient's activity level or rangeof activities by preventing the patient from being active. For example,chronic pain may cause a patient to avoid particular physicalactivities, or physical activity in general, where such activitiesincrease the pain experienced by the patient. Other ailments that mayaffect patient activity include movement disorders such as tremor,Parkinson's disease, multiple sclerosis, epilepsy, or spasticity, whichmay result in irregular movement or activity, other neurologicaldisorders, or a generally decreased level of activity. The difficultywalking or otherwise moving experienced by patients with movementdisorders may cause such patients to avoid movement to the extentpossible. Further, depression or other psychological disorders such asdepression, mania, bipolar disorder, or obsessive-compulsive disorder,congestive heart failure, cardiac arrhythmia, gastrointestinaldisorders, and incontinence are other examples of disorders that maygenerally cause a patient to be less active. When a patient is inactive,he may be more likely to be recumbent, i.e., lying down, or sitting, andmay change postures less frequently.

In some cases, these ailments are treated via a medical device, such asan implantable medical device (IMD). For example, patients may receivean implantable neurostimulator or drug delivery device to treat chronicpain, a movement disorder, or a psychological disorder. Congestive heartfailure and arrhythmia may be treated by, for example, a cardiacpacemaker or drug delivery device.

SUMMARY

In general, the invention is directed to techniques for evaluating atherapy delivered to a patient by a medical device based on postureinformation. At any given time, the medical device delivers the therapyaccording to a current set of therapy parameters. The therapy parametersmay change over time such that the therapy is delivered according to aplurality of different therapy parameter sets. The medical device, oranother device, may identify posture events based on the posture of thepatient, e.g., periodically identify the patient's posture and/orposture transitions. The posture events may be associated with thecurrent therapy parameter set when the event is identified. A value ofat least one posture metric is determined for each of the therapyparameter sets based on the posture events associated with thatparameter set. A list of the therapy parameter sets and associatedposture metrics is presented to a user, such as clinician, forevaluation of the relative efficacy of the therapy parameter sets. Thelist may be ordered according to the posture metric values to aid inevaluation of the therapy parameter sets. In this manner, the user mayreadily identify the therapy parameter sets that support the highestactivity levels for the patient, and evaluate the relative efficacy ofthe parameter sets.

The therapy delivering medical device or another device may monitor oneor more signals that are generated by respective sensors and vary as afunction of patient posture. For example, the medical device or otherdevice may monitor signals generated by a plurality of accelerometers,gyros, or magnetometers. The sensors may be oriented substantiallyorthogonally with each other, and each sensor may be substantiallyaligned with a body axis of the patient. The therapy may be designed totreat a neurological disorder of the patient. Example therapies mayinclude a movement disorder therapy, a psychological disorder therapy,or deep brain stimulation therapy. Specific neurological disorders mayinclude Parkinson's disease or epilepsy.

The medical device or other device may identify a plurality of postureevents based on the one or more signals. In some embodiments, the deviceperiodically identifies the posture of the patient based on the one ormore signals, and the identified posture is stored as a posture event.The device may identify whether the patient is upright or recumbent,e.g., lying down. In some embodiments in which sensors are located at aplurality of positions on or within the body of the patient, the devicemay be able to identify additional postures, such as standing, sittingand recumbent. Example locations for the sensors include on or with thetrunk of the patient, e.g., within an implantable medical device in theabdomen of the patient, and additionally, in some embodiments, on orwithin an upper leg of the patient. In some embodiments, the deviceidentifies transitions between postures, and stores indications ofposture transitions as posture events.

As mentioned above, each posture event may be associated with a currentset of therapy parameters and, for each of a plurality of therapyparameter sets used by the medical device over time, a value of one ormore posture metrics may be determined. A posture metric value may be,for example, an amount or percentage of time spent in a posture while atherapy parameter set is active, e.g., average amount of time over aperiod of time, such as an hour, that a patient was within a particularposture. In some embodiments, a posture metric value may be an averagenumber of posture transitions over a period of time, e.g., an hour, thata particular therapy parameter sets was active.

In embodiments in which a plurality of posture metrics are determinedfor each therapy parameter set, an overall posture metric may bedetermined based on the plurality of posture metrics. The plurality ofposture metrics may be used as indices to select an overall posturemetric from a look-up table comprising a scale of potential overallposture metrics. The scale may be numeric, such as overall posturemetric values from 1-10.

A computing device, such as a programming device, or, in some externalmedical device embodiments, the medical device itself, presents a listof the plurality of parameter sets and associated posture metric valuesvia a display. The computing device may order the list according to theposture metric values. Where values are determined for a plurality ofposture metrics for each of the therapy parameter sets, the programmingdevice may order the list according to the values of a user selected oneof the posture metrics. The computing device may also present otherposture information to a user, such as a trend diagram of identifiedpostures over time, or a histogram or pie chart illustrating percentagesof time that the patient assumed certain postures. The computing devicemay generate such charts or diagrams using posture events associatedwith a particular one of the therapy parameter sets, or all of theposture events identified by the medical device.

In one embodiment, the invention is directed to a method for evaluatingtherapy which includes monitoring a signal generated by a sensor as afunction of posture of a patient and identifying a plurality of postureevents based on the signal. The method also includes associating each ofthe posture events with a therapy parameter set currently used by amedical device to deliver a therapy to the patient when the postureevent is identified, wherein the therapy comprises at least one of amovement disorder therapy, psychological disorder therapy, or deep brainstimulation and determining a value of a posture metric for each of aplurality of therapy parameter sets based posture events associated withthe therapy parameter sets.

In another embodiment, the invention is directed to a medical systemthat includes a medical device that delivers at least one of a movementdisorder therapy, psychological disorder therapy, or deep brainstimulation to a patient and a sensor that generates a signal as afunction of posture of the patient. The medical system also includes aprocessor that monitors the signal generated by the sensor, identifies aplurality of posture events based on the signal, associates each of theposture events with a therapy parameter set currently used by themedical device to deliver the at least one of the movement disordertherapy, psychological disorder therapy, or deep brain stimulation tothe patient when the posture event is identified, and determines a valueof a posture metric for each of a plurality of therapy parameter setsbased posture events associated with the therapy parameter sets.

In an additional embodiment, the invention is directed to a medicalsystem that includes means for delivering at least one of a movementdisorder therapy, psychological disorder therapy, or deep brainstimulation to a patient and means for monitoring a signal generated bya sensor as a function of posture of a patient. The medical system alsoincludes means for identifying a plurality of posture events based onthe signal, means for associating each of the posture events with atherapy parameter set currently used by the means for delivering todeliver the at least one of the movement disorder therapy, psychologicaldisorder therapy, or deep brain stimulation to a patient when theactivity level is determined, and means for determining a value of aposture metric for each of a plurality of therapy parameter sets basedposture events associated with the therapy parameter sets.

The invention is capable of providing one or more advantages. Forexample, a medical system according to the invention may provide aclinician with an objective indication of the efficacy of different setsof therapy parameters. Further, by displaying therapy parameter sets andassociated posture metric values in an ordered and, in some cases,sortable list, the medical system may allow the clinician to more easilycompare the relative efficacies of a plurality of therapy parametersets. The medical system may be particularly useful in the context oftrial neurostimulation for treatment of, for example, chronic pain orneurological disorders, where the patient is encouraged to try aplurality of therapy parameter sets to allow the patient and clinicianto identify efficacious therapy parameter sets.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIGS. 1A and 1B are conceptual diagrams illustrating example systemsthat include an implantable medical device that collects activityinformation according to the invention.

FIGS. 2A and 2B are block diagrams further illustrating the examplesystems and implantable medical devices of FIGS. 1A and 1B.

FIG. 3 is a logic diagram illustrating an example circuit that detectsthe sleep state of a patient from the electroencephalogram (EEG) signal.

FIG. 4 is a block diagram illustrating an example memory of theimplantable medical device of FIG. 1.

FIG. 5 is a flow diagram illustrating an example method for collectingactivity information that may be employed by an implantable medicaldevice.

FIG. 6 is a block diagram illustrating an example clinician programmer.

FIG. 7 illustrates an example list of therapy parameter sets andassociated activity metric values that may be presented by a clinicianprogrammer.

FIG. 8 is a flow diagram illustrating an example method for displaying alist of therapy parameter sets and associated activity metric valuesthat may be employed by a clinician programmer.

FIG. 9 is a conceptual diagram illustrating a monitor that monitorsvalues of one or more accelerometers of the patient instead of, or inaddition to, a therapy delivering medical device.

DETAILED DESCRIPTION

FIGS. 1A and 1B are conceptual diagrams illustrating example systems 10Aand 10B (collectively “systems 10”) that respectively include animplantable medical device (IMD) 14A or 14B (collectively “IMDs 14”)that collect information relating to the posture of a respective one ofpatients 12A and 12B (collectively “patients 12”). In the illustratedexample systems 10A and 10B, IMDs 14 takes the form of an implantableneurostimulator that delivers neurostimulation therapy in the form ofelectrical pulses or signals to a patient 12. However, the invention isnot limited to implementation via an implantable neurostimulator. Forexample, in some embodiments of the invention, IMDs 14 may take the formof an implantable pump or implantable cardiac rhythm management device,such as a pacemaker, that collects posture information. Further, theinvention is not limited to implementation via an IMD. In other words,any implantable or external medical device may collect activityinformation according to the invention.

In the illustrated example, IMDs 14A and 14B delivers neurostimulationtherapy to patients 12A and 12B via leads 16A and 16B, and leads 16B and16D (collectively “leads 16”), respectively. Leads 16A and 16B may, asshown in FIG. 1A, be implanted proximate to the spinal cord 18 ofpatient 12A, and IMD 14A may deliver spinal cord stimulation (SCS)therapy to patient 12A in order to, for example, reduce pain experiencedby patient 12A. However, the invention is not limited to theconfiguration of leads 16A and 16B shown in FIG. 1A or the delivery ofSCS or other pain therapies.

For example, in another embodiment, illustrated in FIG. 1B, leads 16Cand 16D may extend to brain 19 of patient 12B, e.g., through cranium 17of patient. IMD 14B may deliver deep brain stimulation (DBS) or corticalstimulation therapy to patient 12 to treat any of a variety ofnon-respiratory neurological disorders, such as movement disorders orpsychological disorders. Non-respiratory neurological disorders excluderespiratory disorders, such as sleep apnea. Example therapies may treattremor, Parkinson's disease, spasticity, epilepsy, depression orobsessive-compulsive disorder. As illustrated in FIG. 1B, leads 16C and16D may be coupled to IMD 14B via one or more lead extensions 15.

As further examples, one or more leads 16 may be implanted proximate tothe pelvic nerves (not shown) or stomach (not shown), and an IMD 14 maydeliver neurostimulation therapy to treat incontinence or gastroparesis.Additionally, leads 16 may be implanted on or within the heart to treatany of a variety of cardiac disorders, such as congestive heart failureor arrhythmia, or may be implanted proximate to any peripheral nerves totreat any of a variety of disorders, such as peripheral neuropathy orother types of chronic pain.

The illustrated numbers and locations of leads 16 are merely examples.Embodiments of the invention may include any number of lead implanted atany of a variety of locations within a patient. Furthermore, theillustrated number and location of IMDs 14 are merely examples. IMDs 14may be located anywhere within patient according to various embodimentsof the invention. For example, in some embodiments, an IMD 14 may beimplanted on or within cranium 17 for delivery of therapy to brain 19,or other structure of the head of the patient 12.

IMDs 14 delivers therapy according to a set of therapy parameters, i.e.,a set of values for a number of parameters that define the therapydelivered according to that therapy parameter set. In embodiments wherean IMD 14 delivers neurostimulation therapy in the form of electricalpulses, the parameters of each parameter set may include voltage orcurrent pulse amplitudes, pulse widths, pulse rates, duration, dutycycle, and the like. Further, each of leads 16 includes electrodes (notshown in FIG. 1), and a therapy parameter set may include informationidentifying which electrodes have been selected for delivery of pulses,and the polarities of the selected electrodes. In embodiments in whichIMDs 14 deliver other types of therapies, therapy parameter sets mayinclude other therapy parameters such as drug concentration and drugflow rate in the case of drug delivery therapy. Therapy parameter setsused by IMDs 14 may include a number of parameter sets programmed by oneor more clinicians (not shown), and parameter sets representingadjustments made by patients 12 to these preprogrammed sets.

Each of systems 10 may also includes a clinician programmer 20(illustrated as a part of system 10A in FIG. 1A). The clinician may useclinician programmer 20 to program therapy for patient 12A, e.g.,specify a number of therapy parameter sets and provide the parametersets to IMD 14A. The clinician may also use clinician programmer 20 toretrieve information collected by IMD 14A. The clinician may useclinician programmer 20 to communicate with IMD 14A both during initialprogramming of IMD 14A, and for collection of information and furtherprogramming during follow-up visits.

Clinician programmer 20 may, as shown in FIG. 1A, be a handheldcomputing device. Clinician programmer 20 includes a display 22, such asa LCD or LED display, to display information to a user. Clinicianprogrammer 20 may also include a keypad 24, which may be used by a userto interact with clinician programmer 20. In some embodiments, display22 may be a touch screen display, and a user may interact with clinicianprogrammer 20 via display 22. A user may also interact with clinicianprogrammer 20 using peripheral pointing devices, such as a stylus ormouse. Keypad 24 may take the form of an alphanumeric keypad or areduced set of keys associated with particular functions.

Systems 10 may also includes a patient programmer 26 (illustrated aspart of system 10A in FIG. 1A), which also may, as shown in FIG. 1A, bea handheld computing device. Patient 12A may use patient programmer 26to control the delivery of therapy by IMD 14A. For example, usingpatient programmer 26, patient 12A may select a current therapyparameter set from among the therapy parameter sets preprogrammed by theclinician, or may adjust one or more parameters of a preprogrammedtherapy parameter set to arrive at the current therapy parameter set.

Patient programmer 26 may include a display 28 and a keypad 30, to allowpatient 12A to interact with patient programmer 26. In some embodiments,display 28 may be a touch screen display, and patient 12A may interactwith patient programmer 26 via display 28. Patient 12A may also interactwith patient programmer 26 using peripheral pointing devices, such as astylus, mouse, or the like.

Clinician and patient programmers 20, 26 are not limited to thehand-held computer embodiments illustrated in FIG. 1A. Programmers 20,26 according to the invention may be any sort of computing device. Forexample, a programmer 20, 26 according to the invention may be atablet-based computing device, a desktop computing device, or aworkstation.

IMDs 14, clinician programmers 20 and patient programmers 26 may, asshown in FIG. 1A, communicate via wireless communication. Clinicianprogrammer 20 and patient programmer 26 may, for example, communicatevia wireless communication with IMD 14A using radio frequency (RF)telemetry or infrared techniques known in the art. Clinician programmer20 and patient programmer 26 may communicate with each other using anyof a variety of local wireless communication techniques, such as RFcommunication according to the 802.11 or Bluetooth specification sets,infrared communication according to the IRDA specification set, or otherstandard or proprietary telemetry protocols.

Clinician programmer 20 and patient programmer 26 need not communicatewirelessly, however. For example, programmers 20 and 26 may communicatevia a wired connection, such as via a serial communication cable, or viaexchange of removable media, such as magnetic or optical disks, ormemory cards or sticks. Further, clinician programmer 20 may communicatewith one or both of IMD 14 and patient programmer 26 via remotetelemetry techniques known in the art, communicating via a local areanetwork (LAN), wide area network (WAN), public switched telephonenetwork (PSTN), or cellular telephone network, for example.

As mentioned above, IMDs 14 collect patient posture information.Specifically, as will be described in greater detail below, IMDs 14 maymonitor a plurality of signals, each of the signals generated by arespective sensor as a function of patient posture, and may identifyposture events based on the signals. IMDs 14 may, for example,periodically identify the posture of patient 12 or transitions betweenpostures made by patients 12 as posture events. For example, IMDs 14 mayidentify whether the patient is upright or recumbent, e.g., lying down,whether the patient is standing, sitting, or recumbent, or transitionsbetween such postures. IMDs 14 may associate each determined postureevent with the therapy parameter set that is currently active when theposture event is identified.

Over time, IMDs 14 use a plurality of therapy parameter sets to deliverthe therapy to patients 12, and, as indicated above, may associate eachidentified posture event with a current set of therapy parameters. Foreach of a plurality of therapy parameter sets used by IMDs 14 over time,a processor within IMDs 14 or a computing device, such as clinicianprogrammer 20 or patient programmer 26, may determine a value of one ormore posture metrics based on the posture events associated with thattherapy parameter set. A posture metric value may be, for example, anamount or percentage of time spent in a posture while a therapyparameter set is active, e.g., an average amount of time over a periodof time, such as an hour, that patients 12 were within a particularposture. In some embodiments, a posture metric value may be an averagenumber of posture transitions over a period of time, e.g., an hour.

In some embodiments, a plurality of posture metric values are determinedfor each of the plurality of therapy parameter sets. In suchembodiments, an overall posture metric value may be determined. Forexample, the plurality of individual posture metric values may be usedas indices to identify an overall posture metric value from a look-uptable. The overall posture metric may selected from a predeterminedscale of activity metric values, which may be numeric, such as activitymetric values from 1-10.

One or more of IMDs 14 or a computing device may determine the posturemetric values as described herein. In some embodiments, IMDs 14determine and store posture metric values for each of a plurality oftherapy parameter sets, and provide information identifying the therapyparameter sets and the associated posture metric values to a computingdevice, such as programmer 20. In other embodiments, IMDs 14 provideinformation identifying the therapy parameter sets and associatedposture events to the computing device, and the computing devicesdetermine the activity metric values for each of the therapy parametersets using any of the techniques described herein with reference to IMDs14. In still other embodiments, IMDs 14 provide signals output bysensors as function of patient posture to the computing device, or thecomputing devices receive the signals directed from the sensors via awired or wireless link. In such embodiments, the computing device mayidentify posture events and determine posture metric values based on thesignals using any of the techniques described herein with reference toIMDs 14.

In any of these embodiments, programmer 20 may present a list of theplurality of parameter sets and associated posture metric values to theclinician via display 22. Programmer 20 may order the list according tothe posture metric values. Where values are determined for a pluralityof posture metrics for each of the therapy parameter sets, programmer 20may order the list according to the values of one of the posture metricsthat is selected by the clinician. Programmer 20 may also present otherposture information to the clinician, such as a trend diagram of postureover time, or a histogram or pie chart illustrating percentages of timethat the patient assumed certain postures. Programmer 20 may generatesuch charts or diagrams using posture events associated with aparticular one of the therapy parameter sets, or all of the postureevents identified over a period of time.

However, the invention is not limited to embodiments that includeprogrammer 20, or embodiments in which programmer presents postureinformation to the clinician. For example, in some embodiments,programmer 26 presents posture information as described herein to one orboth of the clinician and patients 12. Further, in some embodiments, anexternal medical device comprises a display. In such embodiments, theexternal medical device may both determine posture metric values for theplurality of therapy parameter sets, and presents the list of therapyparameter sets and posture metric values. Additionally, in someembodiments, any type of computing device, e.g., personal computer,workstation, or server, may identify posture events, determine posturemetric values, and/or present a list to a patient or clinician.

FIGS. 2A and 2B are block diagrams further illustrating systems 10A and10B. In particular, FIG. 2A illustrates an example configuration of IMD14A and leads 16A and 16B. FIG. 2B illustrates an example configurationof IMD 14B and leads 16C and 16D. FIGS. 2A and 2B also illustratesensors 40A and 40B (collectively “sensors 40”) that generate signalsthat vary as a function of patient posture. As will be described ingreater detail below, IMDs 14 monitors the signals, and may identifyposture events based on the signals.

IMD 14A may deliver neurostimulation therapy via electrodes 42A-D oflead 16A and electrodes 42E-H of lead 16B, while IMD 14B deliversneurostimulation via electrodes 42I-L of lead 16C and electrodes 42 M-Pof lead 16D (collectively “electrodes 42”). Electrodes 42 may be ringelectrodes. The configuration, type and number of electrodes 42illustrated in FIGS. 2A and 2B are merely exemplary. For example, leads16 may each include eight electrodes 42, and the electrodes 42 need notbe arranged linearly on each of leads 16.

In each of systems 10A and 10B, electrodes 42 are electrically coupledto a therapy delivery module 44 via leads 16. Therapy delivery module 44may, for example, include an output pulse generator coupled to a powersource such as a battery. Therapy delivery module 44 may deliverelectrical pulses to a patient 12 via at least some of electrodes 42under the control of a processor 46, which controls therapy deliverymodule 44 to deliver neurostimulation therapy according to a currenttherapy parameter set. However, the invention is not limited toimplantable neurostimulator embodiments or even to IMDs that deliverelectrical stimulation. For example, in some embodiments a therapydelivery module 44 of an IMD may include a pump, circuitry to controlthe pump, and a reservoir to store a therapeutic agent for delivery viathe pump.

Processor 46 may include a microprocessor, a controller, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field-programmable gate array (FPGA), discrete logiccircuitry, or the like. Memory 48 may include any volatile,non-volatile, magnetic, optical, or electrical media, such as a randomaccess memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM),electrically-erasable programmable ROM (EEPROM), flash memory, and thelike. In some embodiments, memory 48 stores program instructions that,when executed by processor 46, cause IMD 14 and processor 46 to performthe functions attributed to them herein.

Each of sensors 40 generates a signal that varies as a function of apatient 12 posture. IMDs 14 may include circuitry (not shown) thatconditions the signals generated by sensors 40 such that they may beanalyzed by processor 46. For example, IMDs 14 may include one or moreanalog to digital converters to convert analog signals generated bysensors 40 into digital signals usable by processor 46, as well assuitable filter and amplifier circuitry. Although shown as including twosensors 40, systems 10A and 10B may include any number of sensors.

Further, as illustrated in FIGS. 2A and 2B, sensors 40 may be includedas part of IMDs 14, or coupled to IMDs 14 via leads 16. Sensors 40 maybe coupled to IMDs 14 via therapy leads 16A-16D, or via other leads 16,such as lead 16E depicted in FIGS. 2A and 2B. In some embodiments, asensor 40 located outside of an IMD 14 may be in wireless communicationwith processor 46. Wireless communication between sensors 40 and IMDs 14may, as examples, include RF communication or communication viaelectrical signals conducted through the tissue and/or fluid of apatient 12.

Additionally, in some embodiments, sensors 40 may include one or moreelectrodes positioned within or proximate to the brain of patient 12,which detect electrical activity of the brain. For example, inembodiments in which an IMD 14 delivers stimulation or therapeuticagents to the brain, processor 46 may be coupled to electrodes implantedon or within the brain via a lead 16. System 10B, illustrated in FIGS.1B and 2B, is an example of a system that includes electrodes 42,located on or within the brain of patient 12B, that are coupled to IMD14B.

As shown in FIG. 2B, electrodes 42 may be selectively coupled to therapymodule 44 or an EEG signal module 54 by a multiplexer 52, which operatesunder the control of processor 46. EEG signal module 54 receives signalsfrom a selected set of the electrodes 42 via multiplexer 52 ascontrolled by processor 46. EEG signal module 54 may analyze the EEGsignal for certain features indicative of sleep or different sleepstates, and provide indications of relating to sleep or sleep states toprocessor 46. Thus, electrodes 42 and EEG signal module 54 may beconsidered another sensor 40 in system 10B. IMD 14B may includecircuitry (not shown) that conditions the EEG signal such that it may beanalyzed by processor 52. For example, IMD 14B may include one or moreanalog to digital converters to convert analog signals received fromelectrodes 42 into digital signals usable processor 46, as well assuitable filter and amplifier circuitry.

In some embodiments, processor 46 will only request EEG signal module 54to operate when one or more other physiological parameters indicate thatpatient 12B is already asleep. However, processor 46 may also direct EEGsignal module to analyze the EEG signal to determine whether patient 12Bis sleeping, and such analysis may be considered alone or in combinationwith other physiological parameters to determine whether patient 12B isasleep. EEG signal module 60 may process the EEG signals to detect whenpatient 12 is asleep using any of a variety of techniques, such astechniques that identify whether a patient is asleep based on theamplitude and/or frequency of the EEG signals. In some embodiments, thefunctionality of EEG signal module 54 may be provided by processor 46,which, as described above, may include one or more microprocessors,ASICs, or the like.

Sensors 40 may include a plurality of accelerometers, gyros, ormagnetometers that generate signals that indicate the posture of apatient 12. Sensors 40 may be oriented substantially orthogonally withrespect to each other. In addition to being oriented orthogonally withrespect to each other, each of sensors 40 used to detect the posture ofpatient 12 may be substantially aligned with an axis of the body of apatient 12. When accelerometers, for example, are aligned in thismanner, the magnitude and polarity of DC components of the signalsgenerate by the accelerometers indicate the orientation of the patientrelative to the Earth's gravity, e.g., the posture of a patient 12.Further information regarding use of orthogonally aligned accelerometersto determine patient posture may be found in a commonly assigned U.S.Pat. No. 5,593,431, which issued to Todd J. Sheldon.

Other sensors 40 that may generate a signal that indicates the postureof a patient 12 include electrodes that generate a signal as a functionof electrical activity within muscles of the patient 12, e.g., anelectromyogram (EMG) signal, or a bonded piezoelectric crystal thatgenerates a signal as a function of contraction of muscles. Electrodesor bonded piezoelectric crystals may be implanted in the legs, buttocks,chest, abdomen, or back of a patient 12, and coupled to IMDs 14wirelessly or via one or more leads 16. Alternatively, electrodes may beintegrated in a housing of the IMDs or piezoelectric crystals may bebonded to the housing when IMDs are implanted in the buttocks, chest,abdomen, or back of a patient 12. The signals generated by such sensorswhen implanted in these locations may vary based on the posture of apatient 12, e.g., may vary based on whether the patient is standing,sitting, or laying down.

Further, the posture of a patient 12 may affect the thoracic impedanceof the patient. Consequently, sensors 40 may include an electrode pair,including one electrode integrated with the housing of IMDs 14 and oneof electrodes 42, that generates a signal as a function of the thoracicimpedance of a patient 12, and processor 46 may detect the posture orposture changes of the patient 12 based on the signal. The electrodes ofthe pair may be located on opposite sides of the patient's thorax. Forexample, the electrode pair may include one of electrodes 42 locatedproximate to the spine of a patient for delivery of SCS therapy, and IMD14A with an electrode integrated in its housing may be implanted in theabdomen or chest of patient 12A.

Additionally, changes of the posture of a patient 12 may cause pressurechanges with the cerebrospinal fluid (CSF) of the patient. Consequently,sensors 40 may include pressure sensors coupled to one or moreintrathecal or intracerebroventricular catheters, or pressure sensorscoupled to IMDs 14 wirelessly or via lead 16. CSF pressure changesassociated with posture changes may be particularly evident within thebrain of the patient, e.g., may be particularly apparent in anintracranial pressure (ICP) waveform.

Processor 46 may periodically determine the posture of a patient 12, andmay store indications of the determined postures within memory 48 asposture events. Where systems 10 includes a plurality of orthogonallyaligned sensors 40 located on or within the trunk of a patient 12, e.g.,within IMDs 14 which is implanted within the abdomen of a patient 12 asillustrated in FIG. 1, processor 46 may be able to periodicallydetermine whether patient is, for example, upright or recumbent, e.g.,lying down. In embodiments of system 10 that include an additional oneor more sensors 40 at other locations on or within the body of a patient12, processor 46 may be able to identify additional postures of thepatient 12. For example, in an embodiment of systems 10 that includesone or more sensors 40 located on or within the thigh of a patient 12,processor 46 may be able to identify whether the patient 12 is standing,sitting, or lying down. Processor 46 may also identify transitionsbetween postures based on the signals output by sensors 40, and maystore indications of the transitions, e.g., the time of transitions, asposture events within memory 48.

Processor 46 may identify postures and posture transitions by comparingthe signals generated by sensors 40 to one or more respective thresholdvalues. For example, when a patient 12 is upright a DC component of thesignal generated by one of a plurality of orthogonally alignedaccelerometers may be substantially at a first value, e.g., high or one,while the DC components of the signals generated by others of theplurality of orthogonally aligned accelerometers may be substantially ata second value, e.g., low or zero. When a patient 12 becomes recumbent,the DC component of the signal generated by one of the plurality oforthogonally aligned accelerometers that had been at the second valuewhen the patient was upright may change to the first value, and the DCcomponents of the signals generated by others of the plurality oforthogonally aligned accelerometers may remain at or change to thesecond value. Processor 46 may compare the signals generated by suchsensors to respective threshold values to determine whether they aresubstantially at the first or second value, and to identify when thesignals change from the first value to the second value.

Processor 46 may identify posture events continuously or periodically,e.g., one sample of the signals output by sensors 40 every minute orcontinuously for ten minutes each hour. In some embodiments, processor46 limits recording of posture events to relevant time periods, i.e.,when a patient 12 is awake or likely to be awake, and therefore likelyto be active. For example, a patient 12 may indicate via patientprogrammer 26 when patient is going to sleep or awake. Processor 46 mayreceive these indications via a telemetry circuit 50 of IMDs 14, and maysuspend or resume recording of posture events based on the indications.In other embodiments, processor 46 may maintain a real-time clock, andmay record posture events based on the time of day indicated by theclock, e.g., processor 46 may limit posture event recording to daytimehours.

In some embodiments, processor 46 may determine when a patient 12 isattempting to sleep by receiving an indication from patient programmer26. In other embodiments, processor 46 may monitor one or morephysiological parameters of a patient 12 via signals generated bysensors 40, and may determine when the patient 12 is attempting to sleepor asleep based on the physiological parameters. For example, processor46 may determine when the patient 12 is attempting to sleep bymonitoring a physiological parameter indicative of patient physicalactivity. In some embodiments, processor 46 may determine whether apatient 12 is attempting to sleep by determining whether the patient 12remains in a recumbent posture for a threshold amount of time.

In other embodiments, processor 46 determines when a patient 12 isattempting to fall asleep based on the level of melatonin in a bodilyfluid. In such embodiments, a sensor 40 may take the form of a chemicalsensor that is sensitive to the level of melatonin or a metabolite ofmelatonin in the bodily fluid, and estimate the time that the patient 12will attempt to fall asleep based on the detection. For example,processor 46 may compare the melatonin level or rate of change in themelatonin level to a threshold level stored in memory 48, and identifythe time that threshold value is exceeded. Processor 46 may identify thetime that the patient 12 is attempting to fall asleep as the time thatthe threshold is exceeded, or some amount of time after the threshold isexceeded. Any of a variety of combinations or variations of theabove-described techniques may be used to determine when a patient 12 isattempting to fall asleep, and a specific one or more techniques may beselected based on the sleeping and activity habits of a particularpatient.

In order to determine whether a patient 12 is asleep, processor 46 maymonitor any one or more physiological parameters that discernibly changewhen the patient 12 falls asleep, such as activity level, posture, heartrate, electrocardiogram (ECG) morphology, electroencephalogram (EEG)morphology, respiration rate, respiratory volume, blood pressure, bloodoxygen saturation, partial pressure of oxygen within blood, partialpressure of oxygen within cerebrospinal fluid, muscular activity andtone, core temperature, subcutaneous temperature, arterial blood flow,brain electrical activity, eye motion, and galvanic skin response.Processor 46 may additionally or alternatively monitor the variabilityof one or more of these physiological parameters, such as heart rate andrespiration rate, which may discernible change when a patient 12 isasleep. Further details regarding monitoring physiological parameters toidentify when a patient is attempting to sleep and when the patient isasleep may be found in a commonly-assigned and co-pending U.S. patentapplication Ser. No. 11/691,405 by Kenneth Heruth and Keith Miesel,entitled “DETECTING SLEEP,” which was filed Mar. 26, 2007, and isincorporated herein by reference in its entirety.

In other embodiments, processor 46 may record posture events in responseto receiving an indication from patient 12 via patient programmer 26.For example, processor 46 may record posture during times when a patient12 believes the therapy delivered by IMD 14 is ineffective and/or thesymptoms experienced by the patient 12 have worsened. In this manner,processor 46 may limit data collection to periods in which moreprobative data is likely to be collected, and thereby conserve a batteryand/or storage space within memory 48.

FIG. 3 is a logical diagram of an example circuit that detects sleepand/or the sleep type of a patient based on the electroencephalogram(EEG) signal. Alternatively, the circuit may identify an awake state ifa sleep state is not detected. As shown in FIG. 3, module 49 may beintegrated into an EEG signal module of IMDs 14 or a separateimplantable or external device capable of detecting an EEG signal. AnEEG signal detected by electrodes adjacent to the brain of a patent 12is transmitted into module 49 and provided to three channels, each ofwhich includes a respective one of amplifiers 51, 67 and 83, andbandpass filters 53, 69 and 85. In other embodiments, a common amplifieramplifies the EEG signal prior to filters 53, 69 and 85.

Bandpass filter 53 allows frequencies between approximately 4 Hz andapproximately 8 Hz, and signals within the frequency range may beprevalent in the EEG during S1 and S2 sleep states. Bandpass filter 69allows frequencies between approximately 1 Hz and approximately 3 Hz,which may be prevalent in the EEG during the S3 and S4 sleep states.Bandpass filter 85 allows frequencies between approximately 10 Hz andapproximately 50 Hz, which may be prevalent in the EEG during REM sleep.Each resulting signal may then processed to identify in which sleepstate a patient 12 is.

After bandpass filtering of the original EEG signal, the filteredsignals are similarly processed in parallel before being delivered tosleep logic module 99. For ease of discussion, only one of the threechannels will be discussed herein, but each of the filtered signalswould be processed similarly.

Once the EEG signal is filtered by bandpass filter 53, the signal isrectified by full-wave rectifier 55. Modules 57 and 59 respectivelydetermine the foreground average and background average so that thecurrent energy level can be compared to a background level at comparator63. The signal from background average is increased by gain 61 beforebeing sent to comparator 63, because comparator 63 operates in the rangeof millivolts or volts while the EEG signal amplitude is originally onthe order of microvolts. The signal from comparator 63 is indicative ofsleep stages S1 and S2. If duration logic 65 determines that the signalis greater than a predetermined level for a predetermined amount oftime, the signal is sent to sleep logic module 99 indicating thatpatient 12 may be within the S1 or S2 sleep states. In some embodiments,as least duration logic 65, 81, 97 and sleep logic 99 may be embodied ina processor of the device containing EEG module 49.

Module 49 may detect all sleep types for a patient 12. Further, thebeginning of sleep may be detected by module 49 based on the sleep stateof a patient 12. Some of the components of module 49 may vary from theexample of FIG. 3. For example, gains 61, 77 and 93 may be provided fromthe same power source. Module 49 may be embodied as analog circuitry,digital circuitry, or a combination thereof.

In other embodiments, FIG. 3 may not need to reference the backgroundaverage to determine the current state of sleep of a patient 12.Instead, the power of the signals from bandpass filters 53, 69 and 85are compared to each other, and sleep logic module 99 determines whichthe sleep state of patient 12 based upon the frequency band that has thehighest power. In this case, the signals from full-wave rectifiers 55,71 and 87 are sent directly to a device that calculates the signalpower, such as a spectral power distribution module (SPD), and then tosleep logic module 99 which determines the frequency band of thegreatest power, e.g., the sleep state of a patient 12. In some cases,the signal from full-wave rectifiers 55, 71 and 87 may be normalized bya gain component to correctly weight each frequency band.

FIG. 4 illustrates memory 48 of IMDs 14 in greater detail. As shown inFIG. 4, memory 48 stores information describing a plurality of therapyparameter sets 60. Therapy parameter sets 60 may include parameter setsspecified by a clinician using clinician programmer 20. Therapyparameter sets 60 may also include parameter sets that are the result ofpatient 12 changing one or more parameters of one of the preprogrammedtherapy parameter sets. For example, a patient 12 may change parameterssuch as pulse amplitude, pulse frequency, or pulse width via patientprogrammer 26.

Memory 48 also stores thresholds 62 used by processor 46 to identifypostures of patient 12 and/or transitions between postures, as discussedabove. When processor 46 identifies a posture event 64 as discussedabove, processor 46 associates the posture event 64 with the current oneof therapy parameter sets 60, e.g., the one of therapy parameter sets 60that processor 46 is currently using to control delivery of therapy bytherapy module 44 to a patient 12. For example, processor 46 may storedetermined posture event 64 within memory 48 with an indication of theparameter sets 60 with which they are associated. In other embodiments,processor 46 stores samples (not shown) of signals generated by sensors40 within memory 48 with an indication of the parameter sets 60 withwhich they are associated.

In some embodiments, processor 46 determines a value of one or moreposture metrics for each of therapy parameter sets 60 based on theposture events 63 associated with the parameter sets 60. Processor 46may store the determined posture metric values 66 within memory 48 withan indication as to which of therapy parameter sets 60 the determinedvalues are associated with. For example, processor 46 may determine anamount of time that a patient 12 was in a posture when a therapyparameter set 60 was active, e.g., an average amount of time over aperiod of time such as an hour, as a posture metric 66 for the therapyparameter set 60. Processor 46 may additionally or alternativelydetermine percentages of time that patient 12 assumed one or morepostures while a therapy parameter set was active as a posture metric 66for the therapy parameter set 60. As another example, processor 46 maydetermine an average number of transitions over a period of time, suchas an hour, when a therapy parameter set 60 was active as a posturemetric 66 for the therapy parameter set 60.

In some embodiments, processor 46 determines a plurality of posturemetric values 66 for each of the plurality of therapy parameter sets 60,and determines an overall posture metric value 66 for a parameter setbased on the values of the individual posture metrics for that parameterset. For example, processor 46 may use the plurality of individualposture metric values as indices to identify an overall posture metricvalue from a look-up table stored in memory 48. Processor 46 may selectthe overall posture metric value from a predetermined scale of posturemetric values, which may be numeric, such as posture metric values from1-10.

As shown in FIGS. 2A and 2B, IMDs 14 includes a telemetry circuit 50,and processor 46 communicates with programmers 20, 26 via telemetrycircuit 50. In some embodiments, processor 46 provides informationidentifying therapy parameter sets 60 and posture metric values 66associated with the parameter sets to a programmer 20, 26 and theprogrammer displays a list of therapy parameter sets 60 and associatedposture metric values 66. In other embodiments, as will be described ingreater detail below, processor 46 does not determine posture metricvalues 66. Instead, processor 46 provides information describing postureevents 64 to programmer 20, 26 via telemetry circuit 50, and theprogrammer determines posture metric values 66 for display to theclinician. Further, in other embodiments, processor 46 provides samplesof signals generated by sensors 40 to programmer 20, 26 via telemetrycircuit 50, and the programmer may identify both posture events 64 anddetermine posture metric values 66 based on the samples. In still otherembodiments, one of programmers 20, 26 receives one or more of thesignals generated by sensors 40 directly, and the programmer may bothidentify posture events 64 and determine posture metric values 66 basedon the signals. Some external medical device embodiments of theinvention include a display, and a processor of such an external medicaldevice may both determine posture metric values 66 and display a list oftherapy parameter sets 60 and associated posture metric values 66 to aclinician.

FIG. 5 is a flow diagram illustrating an example method for collectingposture information that may be employed by IMDs 14. IMDs 14 monitor aplurality of signals generated by sensors 40 as a function of theposture of patient 12 (70). For example, IMDs 14 may monitor the DCcomponents of signals generated by a plurality of substantiallyorthogonally aligned accelerometers. Each of the accelerometers may besubstantially aligned with a respective axis of the body of a patient12.

IMDs 14 identify a posture event 64 (72). For example, IMDs 14 mayidentify a current posture of a patient 12 at a time when the signalsgenerated by sensors 40 are sampled, or may identify the occurrence of atransition between postures. IMDs 14 identify the current therapyparameter set 60, and associates the identified posture event 64 withthe current therapy parameter set 60 (74). For example, IMDs 14 maystore information describing the identified posture event 64 withinmemory 48 with an indication of the current therapy parameter set 60.IMDs 14 may then update one or more posture metric values 66 associatedwith the current therapy parameter set 60, as described above (76).

IMDs 14 may periodically perform the example method illustrated in FIG.5, e.g., may periodically monitor the posture signals (70), identifyposture events 64 (72), and associate the identified posture events 64with a current therapy parameter set 60 (74). As described above, IMDs14 may only perform the example method during daytime hours, or whenpatient is awake and not attempting to sleep, and/or only in response toan indication received from a patient 12 via patient programmer 26. IMDs14 need not update posture metric values 66 each time a posture event 64is identified, e.g., each time the posture signals are sampled toidentify the posture of a patient 12. In some embodiments, for example,IMDs 14 may store posture events 64 within memory, and may determine theposture metric values 66 upon receiving a request for the values fromclinician programmer 20.

Further, in some embodiments, as will be described in greater detailbelow, IMDs 14 do not determine the posture metric values 66, butinstead provides information describing posture events 64 to aprogramming device, such as clinician programmer 20 or patientprogrammer 26. In such embodiments, the programming device determinesthe posture metric values 66 associated with each of the therapyparameter sets 60. Additionally, as described above, IMDs 14 need notidentify posture events 64. Instead, a programming device may receiveposture signals from IMDs 14 or directly from sensors 40, and may bothidentify posture events 64 and determine posture metric values 66 basedon the samples.

FIG. 6 is a block diagram illustrating clinician programmer 20. Aclinician may interact with a processor 80 via a user interface 82 inorder to program therapy for a patient 12, e.g., specify therapyparameter sets. Processor 80 may provide the specified therapy parametersets to IMDs 14 via telemetry circuit 84.

At another time, e.g., during a follow up visit, processor 80 mayreceive information identifying a plurality of therapy parameter sets 60from IMDs 14 via telemetry circuit 84, which may be stored in a memory86. The therapy parameter sets 60 may include the originally specifiedparameter sets, and parameter sets resulting from manipulation of one ormore therapy parameters by a patient 12 using patient programmer 26. Insome embodiments, processor 80 also receives posture metric values 66associated with the therapy parameter sets 60, and stores the posturemetric values 66 in memory 86.

In other embodiments, processor 80 receives information describingposture events 64 associated with the therapy parameter sets 60, anddetermines values 66 of one or more posture metrics for each of theplurality of therapy parameter sets 60 using any of the techniquesdescribed above with reference to IMDs 14 and FIGS. 2A, 2B, and 4. Instill other embodiments, processor 80 receives the samples of thesignals output by sensors 40 from IMDs 14, or directly from sensors 40,and identifies posture events 64 and determines posture metric values 66based on signals using any of the techniques described above withreference to IMDs 14 and FIGS. 2A, 2B, and 4.

Upon receiving or determining posture metric values 66, processor 80generates a list of the therapy parameter sets 60 and associated posturemetric values 66, and presents the list to the clinician. User interface82 may include display 22, and processor 80 may display the list viadisplay 22. The list of therapy parameter sets 60 may be orderedaccording to the associated posture metric values 66. Where a pluralityof posture metric values are associated with each of the parameter sets,the list may be ordered according to the values of the posture metricselected by the clinician. Processor 80 may also present other postureinformation to a user, such as a trend diagram of posture over time, ora histogram, pie chart, or other illustration of percentages of timethat a patient 12 assumed certain postures. Processor 80 may generatesuch charts or diagrams using posture events 64 associated with aparticular one of the therapy parameter sets 60, or all of the postureevents recorded by IMDs 14.

User interface 82 may include display 22 and keypad 24, and may alsoinclude a touch screen or peripheral pointing devices as describedabove. Processor 80 may include a microprocessor, a controller, a DSP,an ASIC, an FPGA, discrete logic circuitry, or the like. Memory 86 mayinclude program instructions that, when executed by processor 80, causeclinician programmer 20 to perform the functions ascribed to clinicianprogrammer 20 herein. Memory 86 may include any volatile, non-volatile,fixed, removable, magnetic, optical, or electrical media, such as a RAM,ROM, CD-ROM, hard disk, removable magnetic disk, memory cards or sticks,NVRAM, EEPROM, flash memory, and the like.

FIG. 7 illustrates an example list 90 of therapy parameter sets andassociated posture metric values 66 that may be presented by clinicianprogrammer 20. Each row of example list 130 includes an identificationof one of therapy parameter sets 60, the parameters of the therapyparameter set, and values 66 associated with the therapy parameter setfor each of two illustrated posture metrics. Programmer 20 may orderlist 90 according to a user-selected one of the posture metrics.

The posture metrics illustrated in FIG. 7 are a percentage of timeupright, and an average number of posture transitions per hour. IMDs 14or programmer 20 may determine the average number of posture transitionsper hour for one of the illustrated therapy parameter sets byidentifying the total number of posture transitions associated with theparameter set and the total amount of time that IMDs 14 was using theparameter set. IMDs 14 or programmer 20 may determine the percentage oftime upright for one of parameter sets 60 as the percentage of the totaltime that the therapy parameter set was in use that a patient 12 wasidentified to be in an upright position.

FIG. 8 is a flow diagram illustrating an example method for displaying alist of therapy parameter sets 60 and associated posture metric values66 that may be employed by a clinician programmer 20. Programmer 20receives information identifying therapy parameter sets 60 andassociated posture events from IMDs 14 (100). Programmer 20 thendetermines one or more posture metric values 66 for each of the therapyparameter sets based on the posture events 64 associated with thetherapy parameter sets (102). In embodiments in which programmer 20determines posture metric values 66, the clinician may be able tospecify which of a plurality of possible posture metric values 66 aredetermined. In other embodiments, IMDs 14 determine the posture metricvalues 66, and provides them to programmer 20, or provides samples ofposture signals associated with therapy parameter sets to programmer 20for determination of posture metric values, as described above. Afterreceiving or determining posture metric values 66, programmer 20presents a list 90 of therapy parameter sets 60 and associated posturemetric values 66 to the clinician, e.g., via display 22 (104).Programmer 20 may order list 90 of therapy parameter sets 60 accordingto the associated posture metric values 66, and the clinician may selectthe posture metric that list 90 is ordered according to via a userinterface 82 (106).

The invention is not limited to embodiments in which the therapydelivering medical device monitors the posture or other physiologicalparameters of the patient described herein. In some embodiments, aseparate monitoring device monitors the posture or other physiologicalparameters of the patient instead of, or in addition to, a therapydelivering medical device. The monitor may include a processor 46 andmemory 48, and may be coupled to sensors 40, as illustrated above withreference to IMDs 14 and FIGS. 2A, 2B and 4. The monitor may identifyposture events and posture metric values based on the signals receivedfrom the sensors, or may transmit posture events or the signals to acomputing device for determination of posture metric values. In someembodiments, an external computing device, such as a programming device,may incorporate the monitor. The monitor may be external, and configuredto be worn by a patient, such as on a belt around the waist or thigh ofthe patient.

FIG. 9 is a conceptual diagram illustrating a monitor that monitorsvalues of one or more accelerometers of the patient instead of, or inaddition to, such monitoring being performed by a therapy deliveringmedical device. As shown in FIG. 9, patient 12C is wearing monitor 108attached to belt 110. Monitor 108 is capable of receiving measurementsfrom one or more sensors located on or within patient 12C. In theexample of FIG. 9, accelerometers 112 and 114 are attached to the headand hand of patient 12C, respectively. Accelerometers 112 and 114 maymeasure movement of the extremities, or activity level, of patient 12Cto indicate when the patient moves instead of or in addition toidentifying the posture of the patient. Alternatively, more or lessaccelerometers or other sensors may be used with monitor 108. Themovement may be a posture event or other activity that is used todetermine a posture metric.

Accelerometers 112 and 114 may be preferably multi-axis accelerometers,but single-axis accelerometers may be used. As patient 12C moves,accelerometers 112 and 114 detect this movement and send the signals tomonitor 108. High frequency movements of patient 12C may be indicativeof tremor, Parkinson's disease, or an epileptic seizure, and monitor 108may be capable of indicating to IMDs 14, for example, that stimulationtherapy must be changed to effectively treat the patient. In addition,accelerometers 112 and 114 may detect the posture of patient 12C inaddition to or instead of other sensors 40. Accelerometers 112 and 114may be worn externally, i.e., on a piece or clothing or a watch, orimplanted at specific locations within patient 12C. In addition,accelerometers 112 and 114 may transmit signals to monitor 108 viawireless telemetry or a wired connection.

Monitor 108 may store the measurements from accelerometers 112 and 114in a memory. In some examples, monitor 108 may transmit the measurementsfrom accelerometers 112 and 114 directly to another device, such as IMDs14, programming devices 20, 26, or other computing devices. In thiscase, the other device may analyze the measurements from accelerometers112 and 114 to detect efficacy of therapy or control the delivery oftherapy using any of the techniques described herein. In otherembodiments, monitor 108 may analyze the measurements using thetechniques described herein.

In some examples, a rolling window of time may be used when analyzingmeasurements from accelerometers 112 and 114. Absolute values determinedby accelerometers 112 and 114 may drift with time or the magnitude andfrequency of patient 12C movement may not be determined by a presetthreshold. For this reason, it may be advantageous to normalize andanalyze measurements from accelerometers 112 and 114 over a discretewindow of time. For example, the rolling window may be useful indetecting epileptic seizures. If monitor 108 or IMDs 14 detects at leasta predetermined number of movements over a 15 second window, anepileptic seizure may be most likely occurring. In this manner, a fewquick movements from patient 12C not associated with a seizure may nottrigger a response and change in therapy. The rolling window may also beused in detecting changes in posture with accelerometers 112 and 114 orother sensors as described herein.

Various embodiments of the invention have been described. However, oneskilled in the art will recognize that various modifications may be madeto the described embodiments without departing from the scope of theinvention. For example, the invention may be implemented via anyimplantable or external, e.g., non-implantable, medical device, whichmay, but need not, deliver therapy.

As discussed above, the overall activity level of a patient, e.g., theextent to which the patient is on his or her feet or otherwise upright,moving, or otherwise active, rather than sitting, reclining, or lying inplace, may be negatively impacted by any of a variety of ailments orsymptoms. The frequency or amount of time that a patient is withinupright postures, or the frequency of posture changes, may indicate howactive the patient is. Accordingly, such posture metrics, as well asother posture metrics described above, may reflect the efficacy of aparticular therapy or therapy parameter set in treating the ailment orsymptom of the patient. In other words, it may generally be the case asthe efficacy of a therapy parameter set increases, the extent to whichthe patient is active, e.g., the extent or frequency of upright posturesor frequency of posture changes, may increase.

As discussed above, in accordance with the invention, posture events maybe monitored during delivery of therapy according to a plurality oftherapy parameter sets, and used to evaluate the efficacy of the therapyparameter sets. As an example chronic pain may cause a patient to avoidparticular postures, or upright activity in general. Systems accordingto the invention may include any of a variety of medical devices thatdeliver any of a variety of therapies to treat chronic pain, such asSCS, DBS, cranial nerve stimulation, peripheral nerve stimulation, orone or more drugs. Systems may use the techniques of the inventiondescribed above to associate posture events and metrics with therapyparameter sets for delivery of such therapies, and thereby evaluate theextent to which a therapy parameter set is alleviating chronic pain byevaluating the extent to which the patient is upright and/or activeduring delivery of therapy according to the therapy parameter set.

As another example, psychological disorders, and particularlydepression, may cause a patient to be inactive, despite a physicalability to be active. Often, a patient with depression will spend thesignificant majority of his or her day prone, e.g., in bed. Systemsaccording to the invention may include any of a variety of medicaldevices that deliver any of a variety of therapies to treat apsychological disorder, such as DBS, cranial nerve stimulation,peripheral nerve stimulation, vagal nerve stimulation, or one or moredrugs. Systems may use the techniques of the invention described aboveto associate posture events and metrics with therapy parameter sets fordelivery of such therapies, and thereby evaluate the extent to which atherapy parameter set is alleviating the psychological disorder byevaluating the extent to which the therapy parameter set improves theoverall activity level of the patient, e.g., causes the patient to bemore frequently upright or to more frequently change postures.

Movement disorders, such as tremor, Parkinson's disease, multiplesclerosis, spasticity, or epilepsy may also affect the overall activitylevel of a patient, and the extent that the patient is in uprightpostures. In particular, the difficulties associated with performingactivities and movement in general due to the movement disorder maycause a movement disorder patient to simply avoid such activity andspend a significant amount of time prone or seated. In addition, therapymay be directed to reducing or eliminating gait freeze common toParkinson's disease patient. Systems according to the invention mayinclude any of a variety of medical devices that deliver any of avariety of therapies to treat a movement disorders, such as DBS,cortical stimulation, or one or more drugs. Baclofen, which may or maynot be intrathecally delivered, is an example of a drug that may bedelivered to treat movement disorders. Both psychological disorders andmovement disorders may be considered neurological disorders.

Systems may use the techniques of the invention described above toassociate posture events and metrics with therapy parameter sets fordelivery of such therapies. In this manner, such system may allow a userto evaluate the extent to which a therapy parameter set is alleviatingthe movement disorder by evaluating the extent to which the therapyparameter set improves the overall activity level of the patient, e.g.,allows the patient feel able to be upright, moving, and engaging intasks or activities.

Additionally, the invention is not limited to embodiments in which aprogramming device receives information from the medical device, orpresents information to a user. Other computing devices, such ashandheld computers, desktop computers, workstations, or servers mayreceive information from the medical device and present information to auser as described herein with reference to programmers 20, 26. Acomputing device, such as a server, may receive information from themedical device and present information to a user via a network, such asa local area network (LAN), wide area network (WAN), or the Internet.Further, in some embodiments, the medical device is an external medicaldevice, and may itself include a display to present information to auser.

As another example, the invention may be embodied in a trialneurostimulator, which is coupled to percutaneous leads implanted withinthe patient to determine whether the patient is a candidate forneurostimulation, and to evaluate prospective neurostimulation therapyparameter sets. Similarly, the invention may be embodied in a trial drugpump, which is coupled to a percutaneous catheter implanted within thepatient to determine whether the patient is a candidate for animplantable pump, and to evaluate prospective therapeutic agent deliveryparameter sets. Posture metric values collected by the trialneurostimulator or pump may be used by a clinician to evaluate theprospective therapy parameter sets, and select parameter sets for use bythe later implanted non-trial neurostimulator or pump. In particular, atrial neurostimulator or pump may determine values of one or moreposture metrics for each of a plurality of prospective therapy parametersets, and a clinician programmer may present a list of prospectiveparameter sets and associated posture metric values to a clinician. Theclinician may use the list to identify potentially efficacious parametersets, and may program a permanent implantable neurostimulator or pumpfor the patient with the identified parameter sets.

Further, the invention may be embodied as a computer-readable mediumthat includes instructions to cause a processor to perform any of themethods described herein. These and other embodiments are within thescope of the following claims.

What is claimed is:
 1. A method for evaluating therapy comprising:monitoring a signal generated by a sensor as a function of movement of apatient during the delivery of a therapy to the patient by a medicaldevice that delivers the therapy to the patient according to therapyparameters that change over time according to a plurality of therapyparameter sets; identifying a plurality of movement events based on thesignal during the delivery of the therapy to the patient; for eachtherapy parameter set in the plurality of therapy parameter sets,associating each of the movement events in the plurality of movementevents that occur during the delivery of the therapy to the patientaccording that particular therapy parameter set with that particulartherapy parameter set; and for each therapy parameter set in theplurality of therapy parameter sets, determining a value of a metricbased on the movement events associated with that particular therapyparameter set, the value of the metric indicating an efficacy of thatparticular therapy parameter set.
 2. The method of claim 1, whereinidentifying a plurality of movement events comprises identifying amovement indicative of at least one of tremor, Parkinson's disease, oran epileptic seizure.
 3. The method of claim 1, wherein the signalcomprises a signal generated by the sensor as a function of movement ofone or more extremities of the patient.
 4. The method of claim 1,wherein the therapy comprises at least one of a movement disordertherapy, psychological disorder therapy, or deep brain stimulation. 5.The method of claim 4, wherein the therapy comprises at least one of atremor therapy, a Parkinson's disease therapy, and an epilepsy therapy.6. The method of claim 1, further comprising presenting a list of theplurality of therapy parameter sets and metric values associated withthe therapy parameter sets.
 7. The method of claim 6, further comprisingordering the list of therapy parameter sets according to the associatedmetric values.
 8. The method of claim 7, wherein determining a value ofa metric comprises determining a value of each of a plurality of metricsfor each of a plurality of therapy parameter sets based on movementevents associated with the therapy parameter sets, and ordering the listcomprises ordering the list according to a user selected one of themetrics.
 9. The method of claim 1, further comprising presenting agraphical representation of the identified movement events.
 10. Themethod of claim 9, wherein presenting a graphical representationcomprises presenting at least one of a trend diagram, a histogram and apie chart based on the identified movement events.
 11. The method ofclaim 1, wherein the value of the metric represents an activity level ofthe patient.
 12. The method of claim 1, wherein the medical device is animplantable medical device.
 13. The method of claim 1, wherein themedical device includes implantable lead including electrodes, themethod further comprising delivering the therapy to the patient via theelectrodes.
 14. The method of claim 1, wherein the therapy includes deepbrain stimulation, the method further comprising delivering the deepbrain stimulation with the medical device.
 15. The method of claim 1,wherein the therapy includes spinal cord stimulation therapy, the methodfurther comprising delivering the spinal cord stimulation therapy withthe medical device.
 16. The method of claim 1, wherein the therapyincludes pain therapy, the method further comprising delivering the paintherapy with the medical device.
 17. The method of claim 1, wherein thetherapy includes movement disorder therapy, the method furthercomprising delivering the movement disorder therapy with the medicaldevice.
 18. A method for evaluating therapy comprising: monitoring asignal generated by a sensor as a function of movement of a patient;identifying a plurality of movement events based on the signal;associating each of the movement events with a therapy parameter setthat was used by a medical device to deliver a therapy to the patientwhen the movement event was identified; and for each of a plurality oftherapy parameter sets, determining a value of a metric based on themovement events associated with the therapy parameter set, the value ofthe metric indicating an efficacy of the therapy parameter set.
 19. Themethod of claim 18, wherein identifying a plurality of movement eventscomprises identifying a movement indicative of at least one of tremor,Parkinson's disease, or an epileptic seizure.
 20. A method forevaluating therapy comprising: monitoring a signal generated by a sensoras a function of movement of a patient during the delivery of a therapyto the patient by a medical device that delivers the therapy to thepatient according to therapy parameters that change over time accordingto a plurality of therapy parameter sets; identifying a plurality ofmovement events based on the signal during the delivery of the therapyto the patient; for each therapy parameter set in the plurality oftherapy parameter sets, associating each of the movement events in theplurality of movement events that occur during the delivery of thetherapy to the patient according that particular therapy parameter setwith that particular therapy parameter set; and for each therapyparameter set in the plurality of therapy parameter sets, determining avalue of a metric based on the movement events associated with thatparticular therapy parameter set, the value of the metric indicating anobjective efficacy of that particular therapy parameter set.